The goal of this project is to establish the feasibility of using the MinION sequencing platform from Oxford Nanopore in a public health setting, as a tool for outbreak investigation, species identification, strain typing, and antimicrobial resistance prediction using Mycobacterium tuberculosis (Mtb) as a model. Due to many advantages over traditional laboratory testing, Next-generation sequencing (NGS) technologies are being adopted as diagnostic and outbreak investigation tools in larger public health laboratories. However, procurement costs and the need for specialized staff remain as major hurdles for laboratories with limited resources. Lack of portability and turn-around time are also factors influencing the adoption of NGS for certain clinical tests. Recently, Oxford Nanopore developed the MinION, a small hand-held sequencing device. This device offers the advantage of portability, ease of use and faster turn-around time compared to the platform- based NGS options, at a comparable cost per sample. In addition, longer reads averaging in the 10 kilobases can be generated using the MinION, helping for the resolution of repetitive genomic regions and greatly improving genome assemblies. The goal of this proposal is to assess the implementability of MinION sequencing as a diagnostic tool in public health laboratories. Using our current MiSeq whole genome sequencing (WGS) workflow for Mtb as a comparison, we will determine the feasibility of using MinION sequence data for species identification, in silico spoligotyping, accuracy of detecting mutations associated with antimicrobial drug resistance, and phylogenetic analysis to discover transmission routes amongst patients. We will initially perform WGS on the MinION of previously sequenced samples to optimize DNA extraction protocols and library preparation kits, as well as develop and validate a bioinformatics pipeline for data analysis. We will then perform side-by-side real-time sequencing comparison of MiSeq and MinION sequencing for all patient samples received weekly in our center. This research exploits our documented expertise in the utilization of new technologies for clinical diagnostics, bioinformatics pipeline developments, access to clinical specimens for direct testing and implemented NGS workflow for comparisons. Upon completion of this project, we will have developed new methodologies and bioinformatics solutions applied to the implementation of MinION sequencing for clinical diagnostics of pathogens, antimicrobial resistance and identification of outbreak clusters.